{"id":"https://openalex.org/W2085099126","doi":"https://doi.org/10.1117/12.2049814","title":"Variational Bayesian level set for image segmentation","display_name":"Variational Bayesian level set for image segmentation","publication_year":2013,"publication_date":"2013-12-24","ids":{"openalex":"https://openalex.org/W2085099126","doi":"https://doi.org/10.1117/12.2049814","mag":"2085099126"},"language":"en","primary_location":{"id":"doi:10.1117/12.2049814","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2049814","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101793405","display_name":"Hanbing Qu","orcid":"https://orcid.org/0000-0002-5603-8572"},"institutions":[{"id":"https://openalex.org/I4210162962","display_name":"Beijing Academy of Science and Technology","ror":"https://ror.org/05ct4fn38","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210162962"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han-Bing Qu","raw_affiliation_strings":["Beijing Academy of Science and Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Academy of Science and Technology (China)","institution_ids":["https://openalex.org/I4210162962"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lin Xiang","orcid":null},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Xiang","raw_affiliation_strings":["China Jiliang Univ. (China)","China Jiliang University, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Jiliang Univ. (China)","institution_ids":["https://openalex.org/I55538621"]},{"raw_affiliation_string":"China Jiliang University, China#TAB#","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100382043","display_name":"Jiaqiang Wang","orcid":"https://orcid.org/0000-0003-2601-7815"},"institutions":[{"id":"https://openalex.org/I4210162962","display_name":"Beijing Academy of Science and Technology","ror":"https://ror.org/05ct4fn38","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210162962"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia-Qiang Wang","raw_affiliation_strings":["Beijing Academy of Science and Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Academy of Science and Technology (China)","institution_ids":["https://openalex.org/I4210162962"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365157","display_name":"Bin Li","orcid":"https://orcid.org/0000-0002-2332-3959"},"institutions":[{"id":"https://openalex.org/I4210162962","display_name":"Beijing Academy of Science and Technology","ror":"https://ror.org/05ct4fn38","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210162962"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Li","raw_affiliation_strings":["Beijing Academy of Science and Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Academy of Science and Technology (China)","institution_ids":["https://openalex.org/I4210162962"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081002905","display_name":"Haijun Tao","orcid":"https://orcid.org/0000-0002-1513-5640"},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai-Jun Tao","raw_affiliation_strings":["China Jiliang Univ. (China)","China Jiliang University, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Jiliang Univ. (China)","institution_ids":["https://openalex.org/I55538621"]},{"raw_affiliation_string":"China Jiliang University, China#TAB#","institution_ids":["https://openalex.org/I55538621"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19922219,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9067","issue":null,"first_page":"90670D","last_page":"90670D"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9807999730110168,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.756056547164917},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.7227926850318909},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5589506030082703},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5574813485145569},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5539756417274475},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5375044345855713},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.5146323442459106},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5097100734710693},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47751370072364807},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.474540114402771},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4621458947658539},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4401012361049652},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4277638792991638},{"id":"https://openalex.org/keywords/level-set-method","display_name":"Level set method","score":0.4197273850440979},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41608932614326477},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.4122496247291565},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38643577694892883}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.756056547164917},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.7227926850318909},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5589506030082703},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5574813485145569},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5539756417274475},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5375044345855713},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.5146323442459106},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5097100734710693},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47751370072364807},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.474540114402771},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4621458947658539},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4401012361049652},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4277638792991638},{"id":"https://openalex.org/C125269122","wikidata":"https://www.wikidata.org/wiki/Q1751397","display_name":"Level set method","level":4,"score":0.4197273850440979},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41608932614326477},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.4122496247291565},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38643577694892883},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2049814","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2049814","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1979393293","https://openalex.org/W2098152234","https://openalex.org/W2116040950","https://openalex.org/W2155343350","https://openalex.org/W2211248819"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2185902295","https://openalex.org/W2367921179","https://openalex.org/W2945274617","https://openalex.org/W2785294226","https://openalex.org/W657288383","https://openalex.org/W2373659438","https://openalex.org/W4313052709","https://openalex.org/W1879755808","https://openalex.org/W2003543191"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,51,68],"variational":[6],"Bayesian":[7],"framework":[8,71],"for":[9],"level":[10,32,62,90],"set":[11,63,91],"image":[12,24,54,74],"segmentation,":[13],"which":[14],"utilizes":[15],"Gaussian":[16,78],"mixtures":[17,79],"model":[18,73],"to":[19,41,72,88],"approximate":[20,43],"the":[21,30,42,58,61],"posteriors":[22],"of":[23,29,47,53,60],"intensities":[25],"inside":[26],"and":[27,50],"outside":[28],"zero":[31],"set,":[33],"respectively.":[34],"The":[35],"active":[36],"curve":[37],"will":[38],"evolve":[39],"according":[40],"log":[44],"marginal":[45],"probability":[46],"each":[48],"region":[49],"partition":[52],"is":[55,86],"obtained":[56],"by":[57],"sign":[59],"function.":[64],"Our":[65],"method":[66],"provides":[67],"flexible":[69,77],"probabilistic":[70],"data":[75],"with":[76],"model.":[80],"Experimental":[81],"results":[82],"demonstrate":[83],"our":[84],"approach":[85],"comparable":[87],"classical":[89],"segmentation":[92],"method.":[93]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}